Content adaptation is a method to transform the content of a media service according to device and network capabilities. It is especially useful in mobile networks and with mobile devices since the network capabilities varies in different technologies, but also in different locations and time. For example, a user moving in a mobile network will experience different throughput due to change in coverage and change in traffic load, and the traffic load in the network will vary over time.
Examples of media are video, audio and pictures, and the adaptation actions are to transform the media rate of video and audio, and the resolution of pictures.
Adaptive Bit Rate (ABR) streaming is a technique used for streaming media. Today's adaptive streaming techniques are mostly based on Hypertext Transfer Protocol (HTTP). The principle is to encode the media into multiple bit rates, and then to segment each of the encoded media files into smaller chunks. The client is made aware of the available media rates and segment lengths. When streaming the media, the client selects a media rate for each segment that is suitable according to the experienced throughput in the network, and adapts to the changes of throughput. Typically, the client starts to download the first one or few segments at the lowest media rate. If the download bit rate is higher than the media bit rate the client will download the next segment selecting a higher media rate, and so on. Later, if the download bit rate has decreased below the media bit rate, the client will download segments selecting a lower media rate.
Dynamic Adaptive Streaming over HTTP (DASH), also known as Moving Picture Experts Group (MPEG)-DASH is the only HTTP-based adaptive bit rate streaming solution that is an international standard. There are also other HTTP-based adaptive bit rate streaming solutions such as HTTP Live Streaming (HLS).
It is known to provide methods for estimating throughput as described in e.g. WO 2012/118414 and WO 2010/066855.
Today, content adaptation is based on measurements from the download of previous segments as seen from the client in the device, e.g., a User Equipment (UE), which may differ from the current status and the status in the near future in the network. Therefore the decisions taken in the client on content adaptation tend to be more reactive than proactive. In a mobile environment the conditions changes very rapidly, e.g. the UE may change location resulting in a change in radio link quality and throughput. The number of users sharing the same radio resources may decrease or increase also resulting in a change of available throughput for the UE.
Also, a UE fills up the application buffer of a service application for the service based on the buffer status, regardless of the available bandwidth.